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Stance detection in Chinese microblogs with neural networks

  • Nan Yu
  • , Da Pan
  • , Meishan Zhang*
  • , Guohong Fu
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

In this paper, we presents a stance detection system for NLPCC-ICCPOL 2016 share task 4. Our Stance Detection System can determinate whether the author of Weibo text is in favor of the given target, against the given target, or neither. We exploit LSTMs model and the average F score of our system is 56.56%. In contrast to the traditional target/aspect sentiment, the given target may not be preserved in Weibo text. We model the task as a classification problem, exploiting LSTMs as the basic part of classifier.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages893-900
Number of pages8
DOIs
StatePublished - 1 Dec 2016
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10102
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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